06-17421
Imaging and Visualisation Systems

Level 3

Dr P Tiño
Mr R J Hendley

10 credits in Sem2

The School of Computer Science Module Description is a strict subset of this Syllabus Page. (The University module description has not yet been checked against the School's.)

Changes and Updates

Most recent update: 17 Mar 2004.

Changes possible until the start of the academic year.

Outline

Through both lectures and practical work, the module introduces a range of state-of-the-art techniques in the fields of imaging and visualisation. The 'information revolution' has generated large amounts of data, but valuable information is often hidden and hence unusable. Visualisation techniques seek to provide graphical answers to questions such as "How does the data look?", "What structures are there?" or "What model should be used?". Imaging techniques include the generation of realistic models, such as fractal models of landscapes. The module includes some practical work.

Aims

The aims of this module are to:

Introduce the fields of imaging and visualisation.
Investigate the purposes of visualisation and the constraints imposed on visualisation systems.
Explore significant techniques in imaging and visualisation.
Enable students to independently extend the range of techniques that they can use.

Learning Outcomes

On completion of this module, the student should be able to:	Assessed by:
Demonstrate an understanding of the range of imaging and visualisation techniques available.	Examination
Analyse the requirements of visualisation applications.	Examination and coursework
Identify and justify suitable techniques to solve imaging and visualisation problems.	Examination and coursework
Use appropriate tools and techniques to produce visualisation systems.	Coursework
Demonstrate an understanding of the constraints of the human perceptual system.	Examination and coursework

Restrictions, Prerequisites and Corequisites

Restrictions:

Registration is limited to 25 students.

Prerequisites:

06-02504 Graphics 1

Co-requisites:

None

Teaching

Teaching methods:

2 hours/week lectures/exercise classes plus labs

Contact hours:

24+

Assessment

2 hr examination (80%), continuous assessment (20%). Resit (where allowed) by examination only.

Recommended Books

Title	Author(s)	Publisher, Date	Comments
Introduction to Visualisation and Virtual Environments	Chaomei Chen	Springer, 2002
Data Visualization: The state of the art	Frits H. Post, Gregory M. Nielson, Georges-Pierre Bonneau (eds)	Kluwer Academic, 2002
Fractals Everywhere	Michael F. Barnsley	Morgan Kaufmann, 2000

Detailed Syllabus

Introduction (1)
- Motivations for visualisation
- Properties of human perception
- Overview of the range of visualisation techniques and applications
Visualisation of vector and structured data (6)
- Principle Component analysis
- Factor Analysis
- Latent Trait models
- Enhancing the information content of visualisation plots
- Hierarchical visualisation
Fractal Images (4)
- Mandelbrot set
- Julia sets
- Recurrent iterated functions
- Fractal modelling of real world objects
Scientific visualisation (3)
- Isosurfaces, glyphs and other representations
- Languages and techniques
- Examples
Information visualisation (6)
- Features and feature extraction
- Network visualisation
- Text visualisation
- Virtual environments

Relevant Links

Peter Tiño's Module Page

Page maintained by:	Dr P Tiño / Mr R J Hendley
Content last updated:	17 Mar 2004
Source:	/resources/modules/2003/xml/17421.xml

06-17421Imaging and Visualisation Systems